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Interested in hearing how you obtained the proprietary training material for this algo from Apple. Can we see it? Also which teams at apple made the algorithm?

Interested in hearing how you obtained the proprietary training material for this algo from Apple. Can we see it? Also which teams at apple made the algorithm? Since you claim to know they were all 'white'. In reality, I'm sure everyone working on this team was well aware of these potentials for training set bias before most of us even knew what ML was. Even if this was considered it'd be pretty risque to have an employee dedicate time specifically to differentiating black ppl from apes in the algorithm.

jjj123 5y ago
I worked closely with an AI ethicist at $100B+ tech company company and their findings were that all of our AI training data was biased and the ML teams had no plans to de-bias their training data because they had no incentive to do so. I have no reason to believe this finding doesn’t hold for the FAANG companies. AI ethics are mostly an afterthought in tech today. And to your second point about how would we know if the team was “all white,” of course we don’t know that and it’s probably not true. What we do know is that tech in the us is disproportionately whiter than the general public, and ~10 person teams with no black people on them are the norm, not the exception. Edit: I should say that 10 person teams without black people on them are the norm in FAANG companies and others headquartered in the Bay Area. Other tech hubs in the US are much more diverse.
- rscoots 5y ago
  Clearly my point was to highlight your prejudicial instincts around this issue. For all you know the entire team that worked on this project could've been black. Or zero of them could've been white etc. We can and should have a conversation about training sets and ML ethics. Resorting to unprovoked racist attacks is quite a counterproductive approach imo.
- Melchizedek 5y ago
  Tech is not disproportionately white. It’s disproportionately Asian.

jjj123 5y ago

I worked closely with an AI ethicist at $100B+ tech company company and their findings were that all of our AI training data was biased and the ML teams had no plans to de-bias their training data because they had no incentive to do so. I have no reason to believe this finding doesn’t hold for the FAANG companies. AI ethics are mostly an afterthought in tech today. And to your second point about how would we know if the team was “all white,” of course we don’t know that and it’s probably not true. What we do know is that tech in the us is disproportionately whiter than the general public, and ~10 person teams with no black people on them are the norm, not the exception. Edit: I should say that 10 person teams without black people on them are the norm in FAANG companies and others headquartered in the Bay Area. Other tech hubs in the US are much more diverse.

rscoots 5y ago
Clearly my point was to highlight your prejudicial instincts around this issue. For all you know the entire team that worked on this project could've been black. Or zero of them could've been white etc. We can and should have a conversation about training sets and ML ethics. Resorting to unprovoked racist attacks is quite a counterproductive approach imo.
Melchizedek 5y ago
Tech is not disproportionately white. It’s disproportionately Asian.